Background: Changes in myocardial blood flow between rest and stress states are commonly used to diagnose coronary artery disease. Relative myocardial perfusion imaging (MPI) is used routinely while myocardial blood flow quantification (MBF) may improve the sensitivity for detection of early disease. The ratio of flow at stress and rest (S/R) and their difference (S-R) have both been proposed as a means to detect regions with reduced myocardial flow reserve (MFR). In this study, we describe a highly automated method to calculate regional and global rest, stress, S/R, and S-R polar maps of the left ventricle myocardium.
Methods: We measured the inter- and intra-operator variability using two randomized datasets (n = 30 each) for each of two operators (novice and expert) with correlation and Bland-Altman reproducibility coefficient (RPC%) analyses.
Results: S-R MBF had less inter-operator dependent variability than S/R (RPC% = 5.0% vs 12.6%, P < .001). While there was no difference in intra-operator variability with S-R MBF (novice vs expert RPC% = 6.4% vs 5.9%, P = ns), variability was higher in the novice-operator for S/R (RPC% = 16.8% vs 8.5% respectively, P < .001), suggesting that S-R may be preferred for detecting small changes in MFR. The novice operator's intervention pattern became more similar to that of the expert in the later dataset, emphasizing the need for adequate training and quality assurance.
Conclusion: The proposed method results in low operator-dependent variability, suitable for routine use.